Proposal of factor analysis system using probabilistic neural network and application to environmental data
Koji Okuhara, Yukihiro Matsubara, Wataru SHIRAKI, Masataka Gotou · Electronics and Communications in Japan (Part III Fundamental Electronic Science) · 2002
Abstract In this paper we analyze observation data which consist of environmental factors around a creature as the explanatory variables and a population number as the explained variable. We choose data on the firefly. To analyze such data we propose a system incorporating probabilistic neural networks which can acquire an unknown nonlinear mapping from the explanatory variables to the explained variable by using learning. The proposed system can estimate the effect of the explanatory variables on the explained variable, that is, it can solve the inverse problem. To realize the desired environment for the selected creature, we show that our proposed system can suggest an adequate strategy for the controllable explanatory variables. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 85(11): 18–25, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/ecjc.10002